In the financial markets, many traders manage the execution of trades on large portfolios of positions in securities, such as stocks traded on various exchanges. When a trader desires to trade a large number of shares of a specific security, in many instances the trader will employee a Percentage of Volume (POV) trading strategy. In such a strategy, a percentage of the volume to be traded is executed at discrete time intervals throughout a trading period (or trade horizon), such as a trading day. Trading in this way may be beneficial because trading large volumes at once may distort the price for the securities to the disadvantage of the trader. That is, trading large volumes may have a disadvantageous market impact. To simplify this process for the trader, many algorithmic trading systems will automatically place trades for the trader at a given Percentage of Volume (POV) trading rate.
In many instances, a trader attempts to select a portfolio of securities that will maximize the expected return for the portfolio while minimizing the risk in that portfolio. As suggested above, maximizing the expected return for the portfolio may require controlling the market impact of a large trade. Similarly, when executing POV trades, it may be necessary to control the risk to the trader's portfolio due to those trades. Because making a trade that may decrease portfolio risk may also increase market impact, and vice versa, the trader frequently needs to make a trade-off between minimizing market impact while also minimizing portfolio risk. This trade-off is frequently referred to as the Trader's Dilemma.